Rob Snyder

I write software development specifications for software companies. At the moment I’m searching for a software company to pioneer my TGN proposal. The TGN proposal and spec comes from my earlier life building BIMs and creating construction drawings at architecture firms. Years ago that got me into software. I proposed automatic fusion of all construction drawings in-situ at true orientation within BIMs. That led to my invitation to work at Bentley Systems leading the management of the development of “hypermodel”, released in 2012 in MicroStation. The concept has since been repeated by at least 6 other software companies.

My new TGN proposal is the second generation evolution of that earlier work.


Truth is I don’t know if TGN will happen or not. It needs enthusiastic open source advocates and decision makers at software companies who see the potential and want to improve things.

It’s going to take some luck.

I keep knocking on doors.

TGN specification and description:


Modeled environments are extremely complex oceans of information, and the methods/techniques for interpreting them have evolved, to date, inadequately. There are various things like ML and AR/MR and so on, but a generalized approach to sense-making in complex digital environments remains underdeveloped.

This document is a software development specification that addresses the problem. The purpose of the proposed development is to make things clear through ATTENTION-FOCUSING rigs, TGN rigs, within modeled digital environments.

Improved mechanisms of attention-focusing interactive close study of digital models (including digital twins), through TGN rigs, make user engagement with complex data more effective, more interactive, more clarifying, more communicative and expressive, and more revealing of insight. TGN might even bring the fun back into serious technical work by elevating the level of interpretive engagement in digital media. 

It also provides a framework for further interpretation by machine cognition and human interaction with cognitive systems, applied against spatial digital models, via deepQA apps.


TGN: a digital model INTERACTIONS format standard (Apple Book)

TGN: a digital model INTERACTIONS format standard (ePub)

TGN: a digital model INTERACTIONS format standard (iCloud)



0 1 TGN: rigging for insight https://youtu.be/CGXrk9nGj0Y  (2:16)

02 TGN: what is TGN exactly? https://youtu.be/byIW0T8MCsk  (5:35)

03 TGN: demonstration https://youtu.be/wTh2AozTHDc  (3:40)

Self critique of this demo is here:

04 TGN: portability https://youtu.be/Je859_cNvhQ  (5:17)

05 TGN: industry value https://youtu.be/Ka0o1EnGtK4  (9:27)

(the dev platform I mention in the videos is iTwins.js, but TGN can be developed on every platform where TGN is useful and desired)

The industry doesn’t need great new features (nor old features packaged in a very effective new way) siloed in yet another new app. What it needs is a framework for attention-focusing rigs (TGN rigs) within modeled environments of all kinds, with portability of rigs from app to app, platform to platform.

There should be a TGN standard core that’s managed across vendors to support cross platform TGN expression with reliable fidelity. Above the TGN core there can be domain and app-unique TGN enhancements that support TGN rig special functions unique to a domain or vendor app constellation. TGN should ride both waves: a standardization wave and a differentiation wave. The standardized core (ever-evolving), creates a lot of opportunity for a diversity of new differentiation, in existing apps and platforms, and for new apps. Even, I’d say, new apps founded on TGN functionality. Anyone doing this will benefit from the TGN standard core.

Other articles:

https://tangerinefocus.com/2021/11/18/the-future-of-technical-drawing-rev-1/ – a short summary of TGN rig features (including the built-in viewing arc plus the rest of what comprises a TGN rig)

https://tangerinefocus.com/2021/11/09/tgn-a-framework-for-further-interpretation-by-machine-cognition-and-human-interaction-with-cognitive-systems-applied-against-spatial-digital-models-via-deepqa-apps/  – this is for those who want to look further, at what can happen AFTER attention-focusing TGN rigs are in use clarifying models.

In this post is a collection of examples of focused attention and failures of attention, of difficulties in achieving attention, and then, significant risks of communication failure even when attention is achieved, the built-in limitations of human attention, and the necessity of attention nonetheless. If you read this post to the end, I think you’ll appreciate attention in ways that may not have occurred to you before. 

The discussion serves as an introduction to a software development proposal for development of attention-focusing “TGN rigs” within digital modeled environments in industrial domains like mechanical engineering, GIS, and the AECO Architecture, Engineering, Construction and Operations industry.

Try to imagine a person unable to focus, literally unable to pay attention. Imagine an architect, engineer, builder or facility operator unequipped with the tools to articulate focused attention within digital modeled media. Imagine being in this condition because software products omit development of the equipment necessary for users to develop and share their own acts of focused attention within very complex digital worlds. 

What would you say about the maturity of a software industry — and the digital media it produces — devoid of the equipment users require for focusing attention?

TGN is a framework for developing the equipment needed to make sense of and clarify complex digital modeled worlds both during their creation (design) and use (construction and operations). 

The post includes a software development proposal for development of attention-focusing “TGN rigs” within digital modeled environments in industrial domains like mechanical engineering, GIS, and the AECO Architecture, Engineering, Construction and Operations industry.